Digital traces left by active users on social networks have become a popular means of analyzing tourist behavior. The large amount of data generated by tourists provides a key indicator for understanding their behavior according to various criteria. Analyses of tourists’ movement have a crucial role in tourism marketing to build decision-making tools for tourist offices. Those actors are faced with the need to discern tourists’ circulation both quantitatively and qualitatively. In this paper, we propose a measure to capture tourist mobility on various areas which relies on a flow network of data from TripAdvisor into a Neo4j graph database. Thanks to this representation, we produce aggregated graphs at various scales and apply deep tourists’ analysis. One centrality aspect of graphs is used to propose a key indicator of tourists mobility.
21st International Conference on Web Information Systems Engineering (WISE 2020)
Sonia Djebali, Nicolas Loas, and Nicolas Travers